The regulation of eukaryotic genes involves many hundreds of proteins. How they work together at the many thousands of genes that comprise a genome is not known. In order to obtain a comprehensive understanding of how all genes are regulated, we need to know the precise spatial organization, structure, and occupancy levels of all involved proteins. We have developed a genome-wide assay, called ChIP-exo, to measure these aspects of genome regulation, and now propose to develop a higher-throughput version of the assay, and apply it to the mapping of hundreds of genome-binding proteins (aim 1). From this we expect to gain a comprehensive understanding of the structural organization of chromatin and its regulation. The structural information about genomic binding events is woven into the complex patterning of exonuclease stop sites that probe specific DNA contact points. These patterns and their relationships with patterns generated by other proteins often require substantial bioinformatic analyses, which is often out of reach of typical wet-bench scientists. The root of the problem lies at steep learning curve for command-line operations, scripting and proper script application, and keeping data analyses organized. This creates an inherently slow trial-and-error process in biological discovery. Therefore, to alleviate the bottleneck in distillig ChIP-exo data into biological discovery which is so essential to aim 1, we will develop a dedicated and specialized bioinformatic pipeline designed to conduct rapid, easy, and efficient ChIP-exo analyses. Relationships among binding events will provide new insights into transcription complex assembly and regulation. The goal of aim 1 will be to collect ChIP-exo data on 200 yeast potential genome-binding proteins, and their interacting partners or complexes, under multiple cellular states (growth conditions, cell cycle). Tangible outcomes include a precise near-bp map of genomic locations and sub-complex organization, with minimal false positives and negatives. We envision achieving a snapshot of the detailed spatial organization genome- binding proteins at promoters. The goal of aim 2 will be to create a user-friendly, quickly-navigable, platform to execute scripts on ChIP-exo and related data, using our established pipeline. Public use utility of the ChIP-exo datasets will be enhanced with a dedicated platform.